A Nomogram Model that Predicts the Risk of Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients: A Retrospective Study. (9th April 2021)
- Record Type:
- Journal Article
- Title:
- A Nomogram Model that Predicts the Risk of Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients: A Retrospective Study. (9th April 2021)
- Main Title:
- A Nomogram Model that Predicts the Risk of Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients: A Retrospective Study
- Authors:
- Xi, Chunfeng
Wang, Caimei
Rong, Guihong
Deng, Jinhuan - Other Names:
- Perez-Lopez Faustino R. Academic Editor.
- Abstract:
- Abstract : Objective . To construct a novel nomogram model that predicts the risk of diabetic nephropathy (DN) incidence in Chinese patients with type 2 diabetes mellitus (T2DM). Methods . Questionnaire surveys, physical examinations, routine blood tests, and biochemical index evaluations were conducted on 1095 patients with T2DM from Guilin. A least absolute contraction selection operator (LASSO) regression and multivariable logistic regression analysis were used to screen out DN risk factors. A logistic regression analysis incorporating the screened risk factors was used to establish a predictive nomogram model. The performance of the nomogram model was evaluated using the C-index, an area under the receiver operating characteristic curve (AUC), calibration plots, and a decision curve analysis. Bootstrapping was applied for internal validation. Results . Independent predictors for DN incidence risk included gender, age, hypertension, medicine use, duration of diabetes, body mass index, blood urea nitrogen level, serum creatinine level, neutrophil to lymphocyte ratio, and red blood cell distribution width. The nomogram model exhibited moderate prediction ability with a C-index of 0.819 (95% confidence interval (CI): 0.783–0.853) and an AUC of 0.813 (95%CI: 0.778–0.848). The C-index from internal validation reached 0.796 (95%CI: 0.763–0.829). The decision curve analysis displayed that the DN risk nomogram was clinically applicable when the risk threshold was between 1 andAbstract : Objective . To construct a novel nomogram model that predicts the risk of diabetic nephropathy (DN) incidence in Chinese patients with type 2 diabetes mellitus (T2DM). Methods . Questionnaire surveys, physical examinations, routine blood tests, and biochemical index evaluations were conducted on 1095 patients with T2DM from Guilin. A least absolute contraction selection operator (LASSO) regression and multivariable logistic regression analysis were used to screen out DN risk factors. A logistic regression analysis incorporating the screened risk factors was used to establish a predictive nomogram model. The performance of the nomogram model was evaluated using the C-index, an area under the receiver operating characteristic curve (AUC), calibration plots, and a decision curve analysis. Bootstrapping was applied for internal validation. Results . Independent predictors for DN incidence risk included gender, age, hypertension, medicine use, duration of diabetes, body mass index, blood urea nitrogen level, serum creatinine level, neutrophil to lymphocyte ratio, and red blood cell distribution width. The nomogram model exhibited moderate prediction ability with a C-index of 0.819 (95% confidence interval (CI): 0.783–0.853) and an AUC of 0.813 (95%CI: 0.778–0.848). The C-index from internal validation reached 0.796 (95%CI: 0.763–0.829). The decision curve analysis displayed that the DN risk nomogram was clinically applicable when the risk threshold was between 1 and 83%. Conclusion . Our novel and simple nomogram containing 10 factors may be useful in predicting DN incidence risk in T2DM patients. … (more)
- Is Part Of:
- International journal of endocrinology. Volume 2021(2021)
- Journal:
- International journal of endocrinology
- Issue:
- Volume 2021(2021)
- Issue Display:
- Volume 2021, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 2021
- Issue:
- 2021
- Issue Sort Value:
- 2021-2021-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04-09
- Subjects:
- Endocrinology -- Periodicals
Endocrinology
Endocrinology -- Periodicals
Endocrine System Diseases -- Periodicals
Periodicals
616.4 - Journal URLs:
- https://www.hindawi.com/journals/ije/ ↗
http://bibpurl.oclc.org/web/41843 ↗
http://www.ncbi.nlm.nih.gov/pmc/journals/995/ ↗ - DOI:
- 10.1155/2021/6672444 ↗
- Languages:
- English
- ISSNs:
- 1687-8337
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 16646.xml